HomeElectronics NewsWhat's NewAI-Equipped Eyeglasses Can Decipher Unspoken Words

AI-Equipped Eyeglasses Can Decipher Unspoken Words

Researchers have demonstrated a low-power, wearable interface that requires just a few minutes of user training data to recognize silent speech.

System layout and echo profiles. (a-b)Final sensor position and signal paths. S1, S2: speakers; M1, M2: microphones. P1-P4: Paths. Note that each path consists of multiple path reflection and diffraction that originates from the source speaker and ends at the target microphone. The lines in the figure only illustrate the sources and targets. (c) Echo profiles for different utterances. Credit: EchoSpeech: Continuous Silent Speech Recognition on Minimally-obtrusive Eyewear Powered by Acoustic Sensing (2023).
System layout and echo profiles. (a-b)Final sensor position and signal paths. S1, S2: speakers; M1, M2: microphones. P1-P4: Paths. Note that each path consists of multiple path reflection and diffraction that originates from the source speaker and ends at the target microphone. The lines in the figure only illustrate the sources and targets. (c) Echo profiles for different utterances. Credit: EchoSpeech: Continuous Silent Speech Recognition on Minimally-obtrusive Eyewear Powered by Acoustic Sensing (2023).

Individuals unable to produce vocal sounds find it challenging to express themselves. A technology that can restore their speaking ability can benefit them in numerous ways.

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The researchers at Cornell University have developed an unspoken word recognition interface using AI and acoustic-sensing, recognizing up to 31 unvocalized commands from lip and mouth movements. EchoSpeech is a wearable, low-power interface that needs minimal user training data, runs on a smartphone, and can recognize commands.

EchoSpeech enables communication via smartphone in noisy or quiet places and can be paired with a stylus for design software like CAD, reducing the need for a keyboard and mouse.

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EchoSpeech glasses use microphones and speakers smaller than pencil erasers to send and receive sound waves across the face and detect mouth movements. A deep learning algorithm then analyzes these echoes in real-time with 95% accuracy. It advances performance and privacy in wearable tech with small size, low power, and privacy sensitivity, which is critical for real-world deployment.

Most silent-speech recognition technology is usually limited to preset commands and needs camera facing or wearing, which is impractical and infeasible. Privacy concerns arise with wearable cameras for the user and those around them. EchoSpeech’s acoustic-sensing tech eliminates the need for wearable video cameras and requires less bandwidth to process than image or video data. Hence it can be relayed to a smartphone via Bluetooth in real-time.

Researchers believe that privacy-sensitive information always remains in control since the data is processed locally on your smartphone instead of being uploaded to the cloud.

Reference : Conference: chi2023.acm.org/ Research: ruidongzhang.com/files/papers/ … _authors_version.pdf


Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a Senior Technology Journalist at Electronics For You, specialising in embedded systems, development boards, and IoT cloud solutions. With a Master’s degree in Signal Processing, she combines strong technical knowledge with hands-on industry experience to deliver clear, insightful, and application-focused content. Nidhi began her career in engineering roles, working as a Product Engineer at Makerdemy, where she gained practical exposure to IoT systems, development platforms, and real-world implementation challenges. She has also worked as an IoT intern and robotics developer, building a solid foundation in hardware-software integration and emerging technologies. Before transitioning fully into technology journalism, she spent several years in academia as an Assistant Professor and Lecturer, teaching electronics and related subjects. This background reflects in her writing, which is structured, easy to understand, and highly educational for both students and professionals. At Electronics For You, Nidhi covers a wide range of topics including embedded development, cloud-connected devices, and next-generation electronics platforms. Her work focuses on simplifying complex technologies while maintaining technical accuracy, helping engineers, developers, and learners stay updated in a rapidly evolving ecosystem.

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